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在现代高层建筑中,从降低运行成本考虑,由多种互补冷源组成的供冷系统应用得越来越广泛。然而要做到高效节能,如何优化运行是关键问题。为此提出一种基于分布式预测控制的递阶优化策略,首先根据各冷源经济模型和分时电价策略,采用混合整数规划方法,优化各冷源的开启状态及最优功率设定值,同时考虑到各冷源的动态调节特性以及物理约束,提出一种目标耦合的协调分布式预测控制方法,在各子系统MPC目标函数中加入了总体目标,进一步优化各冷源的设定值,使得各冷源在动态过程中保证总负荷的同时跟踪最优制冷量,进一步提高经济性能。该策略以上海某超高层建筑低区供冷系统为对象,通过数值仿真验证了方法的有效性。
In modern high-rise buildings, from the perspective of reducing operating costs, the cooling system composed of a variety of complementary cooling sources has been applied more and more widely. However, to achieve energy efficient, how to optimize the operation is the key issue. To solve this problem, a hierarchical optimization strategy based on distributed predictive control is proposed. First, according to each economic model and time-share price strategy, a mixed integer programming method is adopted to optimize the on-state and optimal power settings of each source. At the same time, considering the dynamic adjustment characteristics and physical constraints of each cold source, a coordinated and distributed control method of target coupling is proposed. The objective of MPC is added into the overall objective of each subsystem to further optimize the settings of each cold source, Making all cold sources in the dynamic process to ensure the total load while tracking the optimal cooling capacity to further improve economic performance. The strategy is based on the cooling system of a low-rise building in Shanghai. The numerical simulation verifies the effectiveness of the method.